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Abstract

Project Summary/Abstract X-ray computed tomography (CT) has been increasingly used in medical diagnosis, currently reaching more than 80 million CT scans every year in the US. The increasing use of CT has sparked concern over the effects of radiation dose on patients. It is estimated that every 2000 CT scans will cause one future cancer, i.e., 40,000 cases of future cancers from 80 million CT scans every year. CT brain perfusion (CTP) is a widely used imaging technique for the evaluation of hemodynamic changes in stroke and cerebrovascular disorders. However, CTP involves high radiation dose for patients as the CTP scan is repeated on the order of 40 times at the same anatomical location, in order to capture the full passage of the contrast bolus. This has been raised as a major concern by the FDA, especially when multiple successive CTPs are performed on the same patient, e.g. to monitor reperfusion following recanalization. Several techniques have been applied for radiation dose reduction in CTP scans, including reduction of tube current and tube voltage, as well as the use of novel noise reduction techniques such as iterative reconstruction (IR). However, the resultant radiation dose of existing CTP scans is still significantly higher than that of a standard head CT scan. The application of IR techniques in CTP is very limited due to the high complexity and computational burden for processing multiple CTP images that may impair clinical workflow. The overarching goal of the present STTR project is to develop and commercialize a novel CT imaging platform that reduces the radiation dose of existing CTP techniques by ~75% without compromising imaging speed or quality. This proprietary technology reduces the radiation dose of CTP scans by controlling the X-ray source to be on intermittently (instead of continuously) at pre-specified rotation angles (i.e., programmed pulsed X-ray). The dynamic CTP image series can then be reconstructed using algorithms that preserve high spatial and temporal resolutions as well as image quality comparable to those of standard CTP scans. During the proposed Phase 1 project, we plan to demonstrate a proof-of-concept of our technology by further developing, optimizing and evaluating the image reconstruction algorithm using both phantom and clinical CTP data. We will also collaborate with CT vendors to ensure the developed technology has a realistic pathway to commercialization.